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Main Authors: Huang, Jiaming, Neri, Luca
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.11195
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author Huang, Jiaming
Neri, Luca
author_facet Huang, Jiaming
Neri, Luca
contents This paper develops a framework for robust identification in SVARs when researchers face a zoo of proxy variables. Instead of imposing exact exogeneity, we introduce generalized ranking restrictions (GRR) that bound the relative correlation of each proxy with the target and non-target shocks through a continuous proxy-quality parameter. Combining GRR with standard sign and narrative restrictions, we characterize identified sets for structural impulse responses and show how to partially identify the proxy-quality parameter using the joint information contained in the proxy zoo. We further develop sensitivity and diagnostic tools that allow researchers to assess transparently how empirical conclusions depend on proxy exogeneity assumptions and the composition of the proxy zoo. A simulation study shows that proxies constructed from sign restrictions can induce biased proxy-SVAR estimates, while our approach delivers informative and robust identified sets. An application to U.S.\ monetary policy illustrates the empirical relevance and computational tractability of the framework.
format Preprint
id arxiv_https___arxiv_org_abs_2601_11195
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Beyond Validity: SVAR Identification Through the Proxy Zoo
Huang, Jiaming
Neri, Luca
Econometrics
This paper develops a framework for robust identification in SVARs when researchers face a zoo of proxy variables. Instead of imposing exact exogeneity, we introduce generalized ranking restrictions (GRR) that bound the relative correlation of each proxy with the target and non-target shocks through a continuous proxy-quality parameter. Combining GRR with standard sign and narrative restrictions, we characterize identified sets for structural impulse responses and show how to partially identify the proxy-quality parameter using the joint information contained in the proxy zoo. We further develop sensitivity and diagnostic tools that allow researchers to assess transparently how empirical conclusions depend on proxy exogeneity assumptions and the composition of the proxy zoo. A simulation study shows that proxies constructed from sign restrictions can induce biased proxy-SVAR estimates, while our approach delivers informative and robust identified sets. An application to U.S.\ monetary policy illustrates the empirical relevance and computational tractability of the framework.
title Beyond Validity: SVAR Identification Through the Proxy Zoo
topic Econometrics
url https://arxiv.org/abs/2601.11195